Land Cover Clustering of NDVI-drived Phenological Features

In this paper, we have considered the method for clustering land cover types over the East Asia from AVHRR data. The feature vectors such that maximum NDVI, amplitude of NDVI, mean NDVI, and NDVI threshold are extracted from the 10-day composite by maximum value composite(MVC) for reducing the effect of cloud contaninations. To find the land cover clusters given by the feature vectors, we are adapted the self-organizing feature map(SOFM) clustering which is the mapping of an input vector space of n-dimensions into a one - or two-dimensional grid of output layer. The approach is to find first the clusters by the first layer SOFM and then merge several clusters of the first layer to a large cluster by the second layer SOFM. In experiments, we were used the 8-km AVHRR data for two years(1992-1993) over the East Asia.